A Statistical Framework for EDF Scheduling

Zhi Ouan; Jong Moon Chung

doi:10.1109/LCOMM.2003.817320

A Statistical Framework for EDF Scheduling

Zhi Ouan, Jong Moon Chung

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

Earliest deadline first (EDF) has become one of the most promising scheduling schemes for providing quality-of-service differentiation over high speed networks. In this letter, we study the deadline violation (loss) probability at an EDF scheduling switch. An analytical framework has been developed for estimating the loss probabilities for the aggregated traffic and the individual flows. This enables us to determine whether a given flow can meet its deadline with the required loss probability. As illustrated from the simulation results using real network traffic, the asymptotic approximations presented are accurate enough to predict the real metrics.

Original language	English
Pages (from-to)	493-495
Number of pages	3
Journal	IEEE Communications Letters
Volume	7
Issue number	10
DOIs	https://doi.org/10.1109/LCOMM.2003.817320
Publication status	Published - 2003 Oct

Bibliographical note

Funding Information:
Manuscript received March 7, 2003. The associate editor coordinating the review of this letter and approving it for publication was Dr. N. A. Nilolaou. This work was supported by the Advanced Networking Research Program of the Oklahoma State University, Stillwater, OK.

All Science Journal Classification (ASJC) codes

Modelling and Simulation
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/LCOMM.2003.817320

Cite this

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title = "A Statistical Framework for EDF Scheduling",

abstract = "Earliest deadline first (EDF) has become one of the most promising scheduling schemes for providing quality-of-service differentiation over high speed networks. In this letter, we study the deadline violation (loss) probability at an EDF scheduling switch. An analytical framework has been developed for estimating the loss probabilities for the aggregated traffic and the individual flows. This enables us to determine whether a given flow can meet its deadline with the required loss probability. As illustrated from the simulation results using real network traffic, the asymptotic approximations presented are accurate enough to predict the real metrics.",

author = "Zhi Ouan and Chung, {Jong Moon}",

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N2 - Earliest deadline first (EDF) has become one of the most promising scheduling schemes for providing quality-of-service differentiation over high speed networks. In this letter, we study the deadline violation (loss) probability at an EDF scheduling switch. An analytical framework has been developed for estimating the loss probabilities for the aggregated traffic and the individual flows. This enables us to determine whether a given flow can meet its deadline with the required loss probability. As illustrated from the simulation results using real network traffic, the asymptotic approximations presented are accurate enough to predict the real metrics.

AB - Earliest deadline first (EDF) has become one of the most promising scheduling schemes for providing quality-of-service differentiation over high speed networks. In this letter, we study the deadline violation (loss) probability at an EDF scheduling switch. An analytical framework has been developed for estimating the loss probabilities for the aggregated traffic and the individual flows. This enables us to determine whether a given flow can meet its deadline with the required loss probability. As illustrated from the simulation results using real network traffic, the asymptotic approximations presented are accurate enough to predict the real metrics.

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A Statistical Framework for EDF Scheduling

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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